Appendix A: ePrOnto: OWL-Based Ontology for Research Information Management

Interoperability is the challenge of getting processes to share and exchange information
effectively. Service orientation relates to creating self-contained, self-describing, accessible,
and open, computer services. Both these challenges relate to the representation of the data
being exchanged/manipulated. There are various existing sources of research information in
the University, for example, ePrints – the publications repository. Research information is
complex, structured data, and the future requirements of it are only partially known. If we
commit to one encoding, or even one representation language, later it may turn out to be
inadequate or obsolete. Current work [10] on these issues points to representing the data in
an ontology.
More specifically, an ontology is a notion defined by Gruber as an explicit specification of a
conceptualization [8]. The term (from the Greek, ontos: of being and logia: study) is
borrowed from Philosophy and it refers to the subject of existence. In Artificial Intelligence
(AI), an ontology is constituted by a specific vocabulary used to describe a certain reality,
plus a set of explicit assumptions regarding the intended meaning of the vocabulary [7].
Thus, the ontology describes a formal specification of a certain domain: a shared
understanding of a domain of interest as well as a formal and machine understandable
model of this domain.
In the e-business context [6], a mechanism to improve system usability, maintenance,
efficiency and interoperability could reside in the formal description of the semantic of the
document-based framework for business collaborations. The formal descriptions could be
provided through the definition of an ontology that represents the implicit concepts and the
relationships that underlie the business vocabulary.